segformerSAAD1
This model is a fine-tuned version of nvidia/mit-b0 on the saad7489/SixGUN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6923
- Mean Iou: 0.6077
- Mean Accuracy: 0.8342
- Overall Accuracy: 0.9596
- Accuracy Bkg: 0.9679
- Accuracy Knife: 0.7929
- Accuracy Gun: 0.7418
- Iou Bkg: 0.9593
- Iou Knife: 0.4467
- Iou Gun: 0.4171
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 23
- eval_batch_size: 23
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Bkg | Accuracy Knife | Accuracy Gun | Iou Bkg | Iou Knife | Iou Gun |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.819 | 20.0 | 20 | 0.9549 | 0.5466 | 0.8951 | 0.9364 | 0.9392 | 0.9027 | 0.8434 | 0.9365 | 0.3263 | 0.3771 |
0.6984 | 40.0 | 40 | 0.6923 | 0.6077 | 0.8342 | 0.9596 | 0.9679 | 0.7929 | 0.7418 | 0.9593 | 0.4467 | 0.4171 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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nvidia/mit-b0